文档介绍：4 基于支持向量机的干散货航运市场运价预警
杨华龙东方
(大连海事大学交通运输管理学院,辽宁大连 116026)
摘要:为分析预测干散货航运市场运价波动的警情,建立基于支持向量机的运价预警模型,并构造相应的算法. 选择BCI、BPI、BSI、BHSI等四个干散货运价指数作为警兆指标,结合航运专家知识经验,确定干散货航运市场运价的实际警度. 依据训练样本数据,利用支持向量机的学习功能,通过编制MATLAB软件程序,获得市场运价警度的分类超平面及预测警度区间,并进行内插和外推检验. 检验结果表明此方法对于干散货航运市场运价预警有很好的适用性.
关键词:干散货航运市场;运价;预警;支持向量机
中图法分类号:, 文献标识码:A
Pre-warning of freight rate in dry bulk shipping market based on support vector machine
YANG Hualong, DONG Fang
(Transportation Management College, Dalian Maritime Univ., Dalian 116026, China)
Abstract: A pre-warning model of freight rate was established based on support vector machine and its algorithm was developed in order to analyze and forecast the alarm of freight rate fluctuation of dry bulk in shipping market. In accordance with shipping experts’ knowledge and experiences, the actual alarm degrees of freight rate within the sample interval of dry bulk in shipping market were determined by BCI, BPI, BSI and BHSI, which were selected as alarm criteria. The classification supper planes and forecasting intervals of freight rate alarm degree of dry bulk in shipping market were obtained by making use of the learning function of support vector machine and programming the MATLAB software based on the training sample data. And then the interpolation and extrapolation examines were carried on. The examination results show that this methodology has a